This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.
Author(s): Virender Kadyan, T. P. Singh, Chidiebere Ugwu
Series: Advanced Technologies and Societal Change
Publisher: Springer
Year: 2023
Language: English
Pages: 253
City: Singapore
Preface
Acknowledgements
Contents
Contributors
1 How Deep Learning Can Help in Regulating the Subscription Economy to Ensure Sustainable Consumption and Production Patterns (12th Goal of SDGs)
Introduction
Why Do We Need Faster and Efficient Manufacturing?
How Long Will We Be Able to Rely on Our Natural Resources for Our Rapid Consumption Demand?
Subscription Services
Mode of Delivery (Online/Offline/Mix)
Payment System (Pay as Use/Periodic)
Limited and Unlimited Subscription
Role of Artificial Intelligence in Subscription Business
Evolution of Deep Learning to Support AI
Paradox: Deep Learning and Sustainable Consumption
Deep Learning as a Solution to Regulate Subscription Economy and Ensuring Sustainable Consumption
Reducing Customer Churn in Subscription of OTT Platforms
Collaborating Internet of Vehicle (IoV) and Deep Learning in Vehicle Subscription
Minimizing Food Wastage and Global Hunger
Convolutional Neural Network (CNN) to Help Shoppers in Identifying Green Products
Regulating the Energy and Water Consumption
Conclusion
Discussions on Findings
Scope for Future Research
Implications for Practitioners
References
2 Deep Technologies Using Big Data in: Energy and Waste Management
Introduction
Deep Learning in Big Data Analytics
Exploiting Deep Learning for Energy Management in Big Data
Introduction
Analytics Model for Energy Management Using Deep Learning
Discussion
Exploiting Deep Learning for Waste Management in Big Data
Introduction
Analysis Model of Waste Management Using Deep Learning
Discussion
Challenges and Prospects: Energy and Waste Management
Summary
References
3 QoS Aware Service Provisioning and Resource Distribution in 4G/5G Heterogeneous Networks
Introduction
Related Work
QoS Provisioning for M2M
Enhanced LTE Network Architecture for 5G Networks
Resource Allocation to Ensure QoS
Adaptive Channel Bandwidth Selection in LTE 4G/5G Networks
System Architecture
Delay Bounded QoS Provisioning
Hybrid Scheduler with QoS Class Identifier
Conclusion
References
4 Leveraging Fog Computing for Healthcare
Introduction
Architecture of Fog Computing
Characteristics of Fog Computing
Applications of Fog Computing
Fog Computing in Healthcare
Healthcare Application Needs
Aim of Fog Computing in HealthCare
Case Studies
The Influence of Healthcare 4.0 with FC in Rural Places
Healthcare 4.0 ECG Monitoring [27]
Patient Training and Monitoring Support [29]
Research Challenges
Conclusion and Future Work
References
5 Intelligent Self-tuning Control Design for Wastewater Treatment Plant Based on PID and Model Predictive Methods
Introduction
Literature Review
Objective of the Work
Proposed Control Methodology
Modelling of Wastewater Treatment Plant
Wastewater Treatment Plant
Activated Sludge Process
Control Techniques
Decentralized PI Controller
PID Controller
Model Predictive Control
Simulation Result and Discussion
Conclusion
Future Scope
References
6 Impact of Deep Learning Models for Technology Sustainability in Tourism Using Big Data Analytics
Introduction
Deep Learning Progress in Tourism
Deep Learning-Based Tourism Models
Deep Learning-Based Recommendation System in Tourism
Deep Learning-Based Tourist Demand Forecasting Model
Deep Learning-Based Sentiment Analysis Models in Tourism Sector
Tourism Sustainability and Covid-19
Application to Facilitate Challenges in Tourism
Impact of Covid-19 on Tourism
Tourism Sustainability: Post Covid-19
Conclusion
References
7 Study of UAV Management Using Cloud-Based Systems
Introduction
Need and Benefits of UAVs
Architecture of Cloud Systems
UAV Monitoring and Management System
Self-allocation Distributed Architecture for Collaborative UAVs
Cloud Computing and Smart Objects
UAV-Cloud Framework Layers
UAV-Cloud Users
UAV-Cloud Elements
UAV-Cloud Platform Architecture
“REST Architecture”
UAV Resources Implementation
Evaluation of Response Time of UAVs
UAV-Cloud Versus Other Related Solution
Conclusion
Future Work
References
8 Contemporary Role of Blockchain in Industry 4.0
Introduction
Literature Review
IIoT
Manufacturing Industry
Blockchain Technology and Industry 4.0
Benefits of Blockchain Technology in Manufacturing Systems
Challenges
Conclusion
References
9 SDGs Laid Down by UN 2030 Document
Introduction
Sustainable Development Goals (SDGs)
Conclusion
Future Scope
References
10 Healthcare 4P: Systematic Review of Applications of Decentralized Trust Using Blockchain Technology
Introduction
Analysis of Blockchain Applications in Removing Barriers for Information Sharing Barriers in Healthcare Sector
Research Methodology
Analysis of Existing Barriers in Healthcare Vertical
Insights of Blockchain Type for Healthcare Sector
Summarized View of Barriers and Applications of Standard Blockchain Types for Healthcare Vertical
Analysis of Blockchain Models for Healthcare Sector
Summary of Conceptual Lens Based on Literature Review
Initial Interview Protocol
Challenges in Information Sharing
Final Interview Protocol Based on Survey Findings
Interview Responses
Review of Challenges Across Blockchain Categories
Contribution to Literature
Conclusion and Future Scope
References
11 Implementation of an IoT-Based Water and Disaster Management System Using Hybrid Classification Approach
Introduction
Related Works
Problem Statement
Proposed Methodology
Result and Discussion
Conclusion
References
12 ANN: Concept and Application in Brain Tumor Segmentation
Introduction
Concept of ANN and Activation Function
Activation Function (Φ)
Steps Involved in ANN
Conclusion
References
13 Automation of Brain Tumor Segmentation Using Deep Learning
Introduction
Convolutional Neural Network
Convolution Layer
Pooling Layer
Fully Connected Layer
Application of CNN in Brain Tumor Segmentation
Conclusion
References
14 Transportation Management Using IoT
Introduction
Under-Utilization of Vehicle Capacity
Route Optimality
Order Tracking
Untimely Delivery of the Consignment
Low Visibility of Inventory and Logistics
Transportation Cost
IoT in Transportation Management
IoT Components and Information Accomplishment
IoT Dimensions in Transportation Management
Basic ANN and Deep Learning [31–33]
Deep Learning Using IoT in Transportation
Traffic Flow Prediction
Traffic Speed Prediction
Travel Time Prediction
Traffic Congestion Prediction
Travel Risk Prediction
Traffic Pollution Monitoring
Parking Occupancy Prediction
Chapter Conclusion and Future Scope
References
15 Enhancing Shoppers’ Loyalty by Prioritizing Customer-Centricity Drivers in the Retail Industry
Introduction
Customer Centricity Drivers
Problem Discussion
Research Methodology
Data Analysis
The Model
Research Implication
Conclusion
References
